Factor Investing

Invesco Global Systematic Investing Study 2023

By focusing on the future landscape, this research offers timely perspectives on how investors are deploying (and looking to deploy) advanced methodologies to construct resilient portfolios and potentially generate alpha.

Welcome to Invesco’s Global Systematic Investing Study 2023. This year, the title of the annual factor investing study has been refreshed, to the Global Systematic Investing Study. This reflects the progression of quantitative investing over the past several years. Since its inception in 2016, the report has provided insights into factor investing. Going forward, the report takes a broader view encompassing the full, and rapidly advancing, systematic investing space.

Systematic investing: the future landscape

Based on interviews with 130 systematic investors, defined as investors that employ structured, rules-based quantitative models and algorithms to make investment decisions, this research collects the opinions of senior decision makers responsible for managing $22.5 trillion in assets (as of March 31, 2023).

Key themes

The research identified four main themes, which the study explored further. These include using systematic strategies to adjust to changing macro environments, the use of Artificial Intelligence (AI) in the investment process, building more flexible systematic strategies and using systematic strategies in sustainable investing.

  • A systematic surge: investors reach for a diverse toolbox in a changing macro environment

    While factor investing has historically been the cornerstone of systematic strategies, investors today are broadening their toolkits and using more diverse strategies (figure 1). As one North American wholesale investor noted: “Traditionally, factor investing has been based around overweighting specific factors such as value and momentum to capture risk premia. Systematic investing now encompasses a broader range of quantitative methodologies.” 

    Figure 1. Systematic methodologies/tools used in portfolio construction, % citations

    Which of the following systematic methodologies/tools are you using in your portfolio construction? Sample size: 130. Grouped by Region Total/APAC/EMEA/North America showing the responses for the tools and methodologies used by respondents. Factor based investing: 94/93/94/94, Dynamic asset allocation: 78/77/73/82, Multi-asset analytics: 51/50/35/67, Systematic risk mitigation using derivatives/options: 51/60/41/55, Quantitative ESG models: 43/63/35/39, Machine learning/AI: 30/50/12/35.

  • The evolution of systematic portfolio construction

    The second theme explores the evolving dynamics of systematic investing.  This study has highlighted the trend towards a more dynamic approach to adjusting factor exposure over the past several years.   We find that nearly three-quarters of respondents adjust through time (figure 2), utilising a broad range of tools to target specific factors at any point.  Additionally, this year’s study has found nearly 80% of respondents view ‘growth’ as an additional factor. 

    Figure 2. Adjust factor weights through time, % citations

    Do you adjust your factor weights through time? Sample size: 130. Chart shows by region responses to whether respondents adjust factor weights through time no/yes. Total: 25/75, APAC: 27/73, EMEA: 14/86, North America: 33/67.

  • Algorithms and alpha: investors look to an Artificial Intelligence-based future

    Data and technology become the focus of the third theme. The rise of Artificial Intelligence (AI) has been noticed by systematic investors, with almost 50% of respondents already implementing some form of AI (figure 3). Adoption is expected to continue and expand across systematic investing practitioners.

    Figure 3. Use of AI in investment process, % citations

    Do you incorporate AI into your investment process? Sample size: 130. Divided by Retail and Wholesale respondents, chart shows the responses split for Use of AI in the investment process for AI used extensively/AI used to a limited extent/Do not use AI but considering/Do not use AI and not considering. Institutional: 10/35/44/11, Wholesale: 8/42/40/10.

  • Investors look to systematic strategies to overcome ESG challenges and meet competing goals

    The fourth, and final theme, for 2023 continues the exploration of systematic investing’s intersection with environmental, social and governance (ESG) investing. Two-thirds of respondents reported using systematic tools in their ESG investing, citing improved performance and risk management as the key drivers (figure 4). The rise of technology from the third theme continues to the fourth, with half of respondents expecting to increase their use of AI and other systematic tools to reconcile data inconsistencies and analyse large data sets more effectively.  

    Figure 4. Advantages of systematic approach to ESG, % citations

    What are the advantages of a systematic approach to applying ESG? Sample size: 100. Chart showing the advantages of systematic approach to ESG split by Total/APAC/EMEA/North America. Improved performance: 77/90/50/89, Improved risk management: 71/83/69/63, Enhanced portfolio diversification: 59/67/53/58, Increased efficiency/lower costs: 39/43/44/32, Improved scalability and capacity: 36/37/34/37, Identification and control of portfolio tilts/bias: 29/23/41/24.

Invesco Global Systematic Investing Study front cover

PDF Invesco Global Systematic Investing Study | Read the full study

By focusing on the future landscape, this research offers timely perspectives on how investors are deploying (and looking to deploy) advanced methodologies to construct resilient portfolios and potentially generate alpha. Read the full study.

Download PDF


Factor investing is a systematic, evidence-based investment approach that targets certain characteristics of an asset, called factors, which tell us something useful about the security’s expected return or risk. It is an investment process based on evidence and empirical research in which every asset return, and hence every portfolio, can be broken down into a set of factors that drive risk and returns. We can specifically structure a portfolio around investment factors. Some of the most common investment factors are value, momentum, quality and low volatility. By investing in assets and portfolios with attractive factor characteristics, investors can aim to earn a premium over the long-term. Factor Investing is the result of profound academic research, starting with the first one-factor model developed in the 1960s.

The idea behind factor investing is to systematically exploit the drivers of risk and return and thereby to generate portfolios that deliver a better risk-return profile. Factor investing can be seen as a third distinct approach alongside market weighted indexing and traditional active. Depending on the application and complexity of the approaches, it usually lies somewhere between the other two options in both expected value-add and cost. It also has key advantages like transparency, scalability, and cost when compared to traditional active approaches, while not giving up the ability to customize, control risk and pursue higher returns as with market cap weighted investing.

Some of the common factors targeted are the following:

Value: cheaply valued stocks are expected to produce higher returns. The simple rationale for the value factor is that it makes sense to expect that buying an asset which is cheaply valued will produce higher subsequent returns than buying when it is expensively valued. The greater return potential of ‘value’ versus its opposite of ‘growth’ was identified by Basu in 1977 and has been widely researched and measured since then.

Momentum: stocks that have performed strongly in the past are expected to continue doing so. The momentum factor describes the phenomenon that stocks that have performed well in the past have tended to continue to do so – at least over the near term. It was first identified in 1993 by Jegadeesh and Titman who found that buying past winners and selling past losers was a strategy that produced excess returns.

Quality: better quality companies expect to produce better returns than lower quality companies. Factor-based strategies address quality by selecting holdings according to balance sheet measures of quality, such as return on equity and financial leverage.

Volatility: low volatility stocks expect to outperform high volatility stocks on a risk-adjusted basis. The rationale for why stocks with historically low volatility may produce higher risk-adjusted returns is that they are typically stable, more defensive companies. Although they may have more limited growth prospects, they tend to have stronger balance sheets, typically pay dividends and can grow earnings and dividends even in a lower economic growth environment. The low volatility factor was first identified in the early 1970s by Haugen and Heins.

The reasons for the existence of factor returns may differ among academics and practitioners but they all have one thing in common: Rationales for investment factors come in one of three forms; risk premia, behavioural anomalies and market structure:

Risk premia: the factor compensates for carrying systematic risk.

Behavioural anomalies: the factor is rooted in persistent, but not necessarily rational investor behaviour.

Market structure: the factor premium potentially results from the structure of the industry, market constraints, or similar.

It can be difficult to establish a definitive link between factor performance and behavioural phenomena, and there is a temptation to use this as a catch-all rationalisation where evidence of risk premia or structural influences have not been demonstrated. Even when investor behaviour does appear, on the surface, to be irrational - this may reflect some other unobserved but rational motivation for the behaviour. For this reason, it cannot be assumed that the market will overcome apparent behavioural anomalies by investors learning to trade more rationally. 

While factor investing is well established in equities, the rationale behind factor investing is not asset class-specific and is equally powerful when applied to fixed income portfolios. It has been seen that there are factors like value, carry and low volatility that can explain the drivers of risk and return of fixed income portfolios. 

Investment risks

  • The value of investments and any income will fluctuate (this may partly be the result of exchange rate fluctuations) and investors may not get back the full amount invested.

Important information

  • This is marketing material and not financial advice. It is not intended as a recommendation to buy or sell any particular asset class, security or strategy. Regulatory requirements that require impartiality of investment/investment strategy recommendations are therefore not applicable nor are any prohibitions to trade before publication. Views and opinions are based on current market conditions and are subject to change. Further information on our products is available using the contact details shown.

Read the 2023 Invesco Global Systematic Investing Study
Explore the rapidly advancing systematic investing space.